Principal components analysis; Number of components; Dimensionality; Eigenvalues; Cattell’s scree plot
Abstract :
[en] Most of the strategies that have been proposed to determine the number of components that account for the most variation in a principal components analysis of a correlation matrix rely on the analysis of the eigenvalues and on numerical solutions. The Cattell’s scree test is a graphical strategy with a nonnumerical solution to determine the number of components to retain. Like Kaiser’s rule, this test is one of the most frequently used strategies for determining the number of components to retain. However, the graphical nature of the scree test does not definitively establish the number of components to retain. To circumvent this issue, some numerical solutions are proposed, one in the spirit of Cattell’s work and dealing with the scree part of the eigenvalues plot, and one focusing on the elbow part of this plot. A simulation study compares the efficiency of these solutions to those of other previously proposed methods. Extensions to factor analysis are possible and may be particularly useful with many low-dimensional components.
Disciplines :
Mathematics
Author, co-author :
Raîche, Gilles
Walls, Ted
Magis, David ; Université de Liège - ULiège > Département de mathématique > Statistique mathématique
Riopel, Martin
Blais, Jean-Guy
Language :
English
Title :
Non-graphical solutions to Cattell's scree test
Alternative titles :
[en] Solutions non-graphiques au test de l'éboulis de Cattell
Publication date :
2013
Journal title :
Methodology: European Journal of Research Methods for the Behavioral and Social Sciences
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